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Related Concept Videos

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Hemodialysis (HD) is a medical treatment that artificially removes waste products, excess fluids, and toxins from the blood when the kidneys are no longer able to perform these functions effectively. In this process, blood is filtered through a semipermeable membrane, allowing for the selective removal of waste while preserving necessary components like blood cells and proteins. Hemodialysis is typically performed in patients with end-stage renal disease (ESRD) or severe kidney...
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DefinitionRenal angiography, also known as renal arteriography, is an imaging technique used to obtain a comprehensive view of blood flow and the vascular structure of blood vessels in the kidneys and surrounding areas.PurposeRenal angiography detects blood vessel abnormalities in the kidneys, such as aneurysms, stenosis, thrombosis, vascular tumors, and renal artery stenosis. It evaluates kidney function and guides interventional treatments like angioplasty or stent placement.Pre-Procedure...
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Mathematical Models for Blood Flow Quantification in Dialysis Access Using Angiography: A Comparative Study.

Nischal Koirala1,2, Gordon McLennan2

  • 1Department of Chemical and Biomedical Engineering, Cleveland State University, Cleveland, OH 44115, USA.

Diagnostics (Basel, Switzerland)
|October 23, 2021
PubMed
Summary

This study introduces an image-based method to measure blood flow in dialysis access using angiography. The cross-correlation algorithm with gamma-variate fitting accurately quantifies flow, aiding in endovascular intervention outcomes.

Keywords:
blood flowbolus tracking algorithmcurve fittingdialysis accessdigital subtraction angiographyfluoroscopyradiation dose

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Area of Science:

  • Medical Imaging
  • Biomedical Engineering
  • Vascular Interventions

Background:

  • Blood flow rate is crucial for assessing dialysis access patency and endovascular intervention success.
  • Currently, no commercial image-based blood flow measurement tools exist for angiography suites.
  • Accurate flow quantification is needed to evaluate and improve dialysis access management.

Purpose of the Study:

  • To develop and evaluate image-based methods for calculating blood flow rate in dialysis access using cine-angiographic and fluoroscopic sequences.
  • To assess the accuracy and variability of different algorithms and curve-fitting models for flow quantification.
  • To determine optimal imaging protocols for computational flow applications in angiography.

Main Methods:

  • Image-based blood flow quantification using digital subtraction angiography (DSA) and fluoroscopy in a flow phantom model.
  • Employed bolus tracking algorithms (peak-to-peak, cross-correlation) and curve-fitting functions (gamma variate, lagged normal, polynomial).
  • Calculated dye propagation distance and cross-sectional area from contrast enhancement; correlated results with an in-line flow sensor.

Main Results:

  • The cross-correlation algorithm with gamma-variate fitting demonstrated the best accuracy and least variability in both DSA and fluoroscopy modes.
  • At 6 frames/s DSA, the absolute percent error was 21.4 ± 1.9%; at 10 pulses/s fluoroscopy, it was 37.4 ± 3.6%.
  • Optimal performance was achieved with DSA at 6 frames/s, showing the best correlation with flow sensor measurements; radiation dose was low.

Conclusions:

  • Image-based blood flow measurement in dialysis access is feasible using angiography.
  • The cross-correlation algorithm combined with gamma-variate fitting provides accurate flow quantification.
  • These findings support the development of software tools for angiography suites to optimize vascular access management and intervention outcomes.